Trusting Your AI Agent Emotionally and Cognitively: Development and Validation of a Semantic Differential Scale for AI Trust

However, a critical gap exists in the lack of generalizable and accurate specialized measurement tools Trust plays a crucial role not only in fostering cooperation, for assessing affective trust in the context of AI, especially efficiency, and productivity in human relationships (Brainov with the enhanced and nuanced capabilities of LLMs. This and Sandholm 1999) but also is essential for the effective highlights a need for a better measurement scale for affective use and acceptance of computing and automated systems, trust to gain a deeper understanding of how trust dynamics including computers (Madsen and Gregor 2000), automation function, particularly in the context of emotionally intelligent (Lee and See 2004), robots (Hancock et al. 2011), and AI. AI technologies (Kumar 2021), with a deficit in trust potentially In this paper, we introduce a 27-item semantic differential causing rejection of these technologies (Glikson and scale for assessing cognitive and affective trust in AI, Woolley 2020). The two-dimensional model of trust, encompassing aiding researchers and designers in understanding and improving both cognitive and affective dimensions proposed human-AI interactions. Our motivation and scale and studied in interpersonal relationship studies (McAllister development process is based on a long strand of prior research 1995; Johnson and Grayson 2005; Parayitam and Dooley on the cognitive-affective construct of trust that has 2009; Morrow Jr, Hansen, and Pearson 2004), have been shown to be important in interpersonal trust in organizations, been adopted in studying trust in human-computer interactions, human trust in conventional technology and automation, particularly with human-like technologies (Hu, Lu and more recently in trust towards AI.